Spatial and temporal variations of physicochemical and heavy metal pollution in Ramganga River—a tributary of River Ganges,India

The River Ganges being the most sacred river and lifeline to millions of Indians in serving their water requirements is facing excessive threat of pollution. Under various river management and conservation strategies for its protection, the assessment of water quality of its main tributary Ramganga River is lacking. This study focuses on assessment of physicochemical and heavy metal pollution of the Ramganga River by application of multivariate statistical techniques. Sampling of Ramganga River at sixteen sampling sites was carried out in three seasons (summer, monsoon and winter) of 2014. The collected water samples were analyzed for physicochemical parameters and heavy metals. Results from cluster analysis (CA) of the data divided the whole stretch of the river into three clusters as elevation from 1304 to 259 m as less polluted, from 207 to 154 m as moderately polluted and from elevation 154 to 139 m as high-polluted stretches with anthropogenic as main sources of pollution in high-polluted stretch. Principal component analysis of the seasonal dataset resulted in three significant principal components (PC) in each season explaining 72–8% of total variance with strong loadings (>0.75) of PC1 on fluoride (F^?), chloride (Cl^?), sodium (Na⁺), calcium (Ca²⁺), magnesium (Mg²⁺), bicarbonate (HCO₃ ^?), total dissolved solids and electrical conductivity. Temporal variation by one-way ANOVA (Analysis of Variance) showed significant seasonal variation was in the pH, chemical oxygen demand, biochemical oxygen demand, turbidity, HCO₃ ^?, F^?, Zn, cadmium (Cd) and Mn (p < 0.05). Turbidity showed approximately a twofold increase in monsoon season due to rainfall in the catchment area and subsequent flow of runoff into the river. Concentration of HCO₃ ^?, F^? and pH also showed similar increase in monsoon. The concentration of Zn, Cd and Mn showed an increasing trend in summers compared to monsoon and winter season due to dilution effect in the monsoon season and its lasting effect in winters.     

GPR survey and physical measurements of sea ice in Quilty Bay,Larsemann hills,East Antarctica and its correlation with local atmospheric parameters

Sea ice formation in Quilty Bay, East Antarctica shows a strong relationship with climatic conditions and its spatial variation is established by GPR survey over the sea ice during the austral winters. The study also evaluates the variability of sea ice thickness and extent with local weather parameters between 2010 and 2014. Profiling on sea ice in Quilty Bay shows that sea ice thickness decreases gradually towards east. The overall thickness of sea ice is considerably less at the centre of the bay as compared to the coastal side. Two types of fast ice layers have been delineated from GPR surveys i.e. top layer fast ice which incorporates very low density surface snow and underlying high density fast ice i.e. with melt water pockets. Development of sea ice is influenced by persistent easterly winds, temperature fluctuations and ocean currents. Sea ice reveal average annual cyclic trend in Quilty Bay with maximum development in the year 2013 (157.54 cm) and the minimum development has been observed in the year 2010 (99.04 cm).The cyclic pattern of average sea ice accumulation data show perfect inverse correlation with surface air temperature, with measure of reliability R² = 0.93. However, moderate (R² = 0.52) and good (R² = 0.69) degree of inverse relationship is observed with surface snow and overall sea ice (snow and ice) respectively. With 0.46 °C change in temperature, there is 33% change in sea ice condition in Quilty Bay which may remain same as far as ice extents in the region. Besides this easterly winds play a vital role in controlling the snow/ice distribution patterns as reflected by isopach maps.     

The deuterium and oxygen-18 isotopic composition of the groundwater in Khan Younis City,southern Gaza Strip (Palestine)

The environmental isotopes such as deuterium and oxygen-18 and the deuterium excess values have been used to assess groundwater recharge sources and their dynamics in Khan Younis City in the Gaza Strip in Palestine. Three isotopic lines for the relationship between δ²H and δ¹⁸O were used in the assessment. These lines are the global meteoric water line, the local meteoric water line and the groundwater evaporation line. The δ²H, δ¹⁸O and D-excess values indicate that deuterium and oxygen-18 isotopes originated in the groundwater from groundwater mixing with rainfall and other water sources; the groundwater in the area recharged from rainfall from a distant source that came from the Mediterranean Sea and from other sources such as wastewater, irrigation return flow and saline water.     

Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed,India

Abstract

The process-based Soil and Water Assessment Tool (SWAT) model and the data-driven radial basis neural network (RBNN) model were evaluated for simulating sediment load for the Nagwa watershed in Jharkhand, India, where soil erosion is a severe problem. The SWAT model calibration and uncertainty analysis were performed with the Sequential Uncertainty Fitting algorithm version 2 and the bootstrap technique was applied on the RBNN model to analyse uncertainty in model output. The percentage of data bracketed by the 95% prediction uncertainty (95PPU) and the r factor were the two measures used to assess the goodness of calibration. Comparison of the results of the two models shows that the value of r factor (r = 0.41) in the RBNN model is less than that of SWAT model (r = 0.79), which means there is a wider prediction interval for the SWAT model results. More values of observed sediment yield were bracketed by the 95PPU in the RBNN model. Thus, the RBNN model estimates the sediment yield values more accurately and with less uncertainty.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Singh, A., Imtiyaz, M., Isaac, R.K., and Denis, D.M., 2014. Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed, India. Hydrological Sciences Journal, 59 (2), 351–364.     

Identification of homogenous regions in Gorganrood basin (Iran) for the purpose of regionalization

Estimation of flood in basins with poor condition of hydrometric stations as in quantity and quality is a dominant problem around the world, mainly in developing country where lack of funds and human resources cause more limitation in number of gauging stations. One of the areas that experience frequent floods and also suffer from small number of stations in Iran is Gorganrood basin. So there is a great need for the estimation and prediction of runoff in this area to prevent any future floods. Due to insufficient station in this area, direct prediction of flood is not applicable. Regional flood frequency analysis is a practical and widely used solution for these situations, which involves the identification of homogenous regions. Gorganrood region was hydrologically homogenized according to the extracted parameters that influence the floods. One of these parameters was Normalized Difference Vegetation Index (NDVI) driven from MODIS images. Curvature is another parameter that relates to topographic attributes. From factor analysis, the most appropriate variables were selected. According to these parameters (NDVI, curvature, area, slope…), the regions were classified into homogenous regions. For the purpose of homogenization, hierarchical (wards) clustering, fuzzy clustering and Kohonen method were applied. L-moment technique was used for the investigation of the results. The heterogeneity measure for one of the groups (Group 1) was more than two; therefore some modifications were applied. The region was grouped into two homogenous subregions. All of the clustering methods showed same results. The models showed that class 4 of NDVI is influential on flood in some return periods. The resulted models can be applied in future studies in different aspects of practical hydrology.     

Effect on physico-chemical and structural properties of soil amended with distillery effluent and ameliorated by cropping two cereal plant spp.

Molasses-based distilleries are one of the most polluting industries generating large volume of wastewater. Distillery effluent (DE) on its discharge alters the physical and chemical properties of the soil. This study has been conducted to assess the distribution of heavy metals and its effect on physiochemical and structural changes of soil which has been treated with diluted and undiluted effluents. The soil has been assayed both before and after crop plantation. Out of the crop plants studied, Cicer arietinum was least effected and more effective than Pisum sativum in diminishing the heavy metals from soil. However, only at higher concentration DE has some adverse impact on the nutrient contents of the soil. Fourier transform infrared spectrum (FTIR) study of the soil indicated the presence of –OH, –NH, –COOH groups. It was also noted that the soil amended with different concentration of DE and on which Cicer and Pisum were grown has varied IR spectrum. These variations show the presence of different functional groups of soil before and after plants were grown. The presence of inorganic carbonate was found in soil planted with Cicer from 10 to 50% of DE, whereas aliphatic primary amides were observed up to 25 and 100% concentrations of DE in soil planted with Pisum. The appearance of inorganic nitrates, carbonates, aliphatic hydrocarbons and aliphatic primary amides at various concentrations of DE showed a change in functional groups probably because of the differential breakdown of parent component present in the effluent. Besides our main finding that Cicer is a very useful crop species in remediating the soil which has inflicted with even undiluted DE, it is also validated through FTIR spectra that IR technique is an efficient tool in studying the structural changes of soil and with some degree of caution may be summed up that FTIR may be used to correlate the relative efficacy of plants to transform organic contaminants.     

Land transformation assessment using the integration of remote sensing and GIS techniques: a case study of Al-Anbar Province,Iraq

Human activities and climate changes significantly affect our environment, altering hydrologic cycles. Several environmental, social, political, and economical factors contribute to land transformation as well as environmental changes. This study first identified the most critical factors that affect the environment in Al-Anbar city including population growth, urbanization expansion, bare land expansion, and reduction in vegetation cover. The combination of remote sensing data and fuzzy analytic hierarch process (Fuzzy AHP) enabled exploration of land transformations and environmental changes in the study area during 2001 to 2013 in terms of long and short-term changes. Results of land transformation showed that the major changes in water bodies increased radically (94 %) from the long-term change in 2001 to 2013 because of water policies. In addition, the urban class expanded in two short-term periods (2001–2007 and 2007–2013), representing net changes of 46 and 60 %, respectively. Finally, barren land showed 25 % reduction in the first period because of the huge expansion of water in the lake; a small percentage of growth gain was observed in the second period. Based on the land transformation results, the environmental degradation assessment showed that the study area generally had high level of environmental degradation. The degradation was mostly in the center and the north part of the study area. This study suggested for further studies to include other factors that also responsible for environmental degradation such as water quality and desertification threatening.     

Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island,Malaysia

Land surface temperature (LST) plays an important role in local, regional and global climate studies. LST controls the distribution of the budget for radiation heat between the atmosphere and the earth’s surface. Therefore, it is important to evaluate abrupt changes in land use/land cover (LULC). Penang Island, Malaysia has been experiencing a rapid and drastic change in urban expansion over the past two decades due to growth in industrial and residential areas. The aim of this study was to investigate and evaluate the impact of LST with respect to land use changes in Penang Island, Malaysia. Three supervised classification techniques known as maximum likelihood, minimum distance-to-mean and parallelepiped were applied to the images to extract thematic information from the acquired scene by using PCI Geomatica 10.1 image processing software. These remote sensing classification techniques help to examine land-use changes in Penang Island using multi-temporal Landsat data for the period of 1999–2007. Training sites were selected within each scene and seven land cover classes were assigned to each classifier. The relative performance of each technique was evaluated. The accuracy of each classification map was assessed using a reference data set consisting of a large number of samples collected per category. Two Landsat satellite images captured in 1999 and 2007 were chosen to classify the LULC types using the maximum likelihood classification method, determined from visible and near-infrared bands. The study revealed that the maximum likelihood classifier produced superior results and achieved a high degree of accuracy. The LST and normalised difference vegetation index (NDVI) were computed based on changes in LULC. The results showed that the urban (highly built-up) area increased dramatically, and grassland area increased moderately. Inversely, barren land decreased obviously, and forest area decreased moderately. While urban (minimally built-up) area decreased slightly. These changes in LULC caused at significant difference in LST between urban and rural areas. Strong correlation values were observed between LST and NDVI for all LULC classes. The remote sensing technique used in this study was found to be efficient; it reduced the time for the analysis of the urban expansion, and it was found to be a useful tool to evaluate the impact of urbanisation with LST.     

Mechanical response of saturated and unsaturated gravels of different sizes in drained triaxial testing

Acta Geotechnica - During the construction of pavements, gravelly soil is used as the main material in the base and sub-base layers. Predicting the deformation behaviour of gravelly soil has been...